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This community service program aims to enhance public awareness and skills in managing household waste through an innovative recycling-based approach. The main problems identified in the target community include limited understanding of waste segregation, lack of knowledge regarding the economic potential of household waste, and insufficient skills to transform waste materials into useful products. To address these issues, the program was implemented through several stages, including an initial survey to identify community needs, environmental education and awareness sessions, hands-on training on producing recycled products, and continuous mentoring to ensure the sustainability of the activities.The results show a significant increase in participants’ knowledge of proper waste management and recycling concepts. Moreover, the community successfully produced various creative and functional recycled items such as plant pots, household crafts, and other aesthetically valuable products with economic potential. The program also facilitated the establishment of a resident group committed to continuing the initiative independently. Overall, this community service activity demonstrates that practical environmental education can effectively foster ecological awareness, strengthen community participation, and create opportunities for local economic empowerment through the utilization of household waste.

The popularity of the boys love (BL) genre, a key representation of the LGBTQ community, raises concerns about its potential negative impact on social pathology related to LGBTQ behaviors among fans. Despite the stigma labeling BL enthusiasts as exhibiting deviant sexual behavior (homosexuality), early observations and field findings show that most fans are heterosexual and do not exhibit such behavior. Instead, their engagement represents a cumulative effort to support LGBTQ representation. This research uses a qualitative case study approach, conducted on social media X over four months. Key findings suggest that the primary curative efforts by fans to address the social pathology of LGBTQ are self-control and the establishment of self-boundaries. Self-control is demonstrated through cognitive and decision-making control, while self-boundaries are seen in fans' understanding that fictional content should not be translated into heteronormative reality. Strengthening self-control and self-boundaries lays the foundation for further curative actions, preventing fans from becoming fully integrated into the LGBTQ community.

This community engagement program aims to strengthen the halal value chain of micro, small, and medium enterprises (MSMEs) in Hagu Selatan Village, Banda Sakti District, Lhokseumawe City through knowledge transfer based on the Indonesian halal value chain model. MSMEs play a vital role in regional economic development, yet many still face challenges in understanding halal–thayyiban principles, fulfilling certification requirements, managing production processes, and accessing Islamic financing. Limited adoption of digitalization also reduces their competitiveness in the rapidly growing halal industry. The program applies a participatory approach by involving universities, village authorities, and MSMEs. Key activities include needs assessment, training on halal value chain concepts, technical assistance for halal certification documents, workshops on digital business practices, and business clinics on Islamic financing. A Halal Value Chain Learning Circle is also established to support continuous collaboration and knowledge sharing. The program is expected to enhance MSME capacity, improve product quality, expand market access, and contribute to a sustainable halal ecosystem in Aceh.

This community service was carried out at SMAS PGRI 1 Mojokerto City with the main goal of improving student discipline through the application of Japanese-style discipline culture. This activity is designed in a structured manner to have a real and sustainable impact on student behavior and the integrity of educational institutions. The method used is a participatory and applicative approach, so that students not only passively receive information, but also actively engage in the process of learning, reflection, and discipline practice. This approach emphasizes the direct involvement of students in activities that foster awareness, responsibility, and positive habits that support the creation of a conducive learning environment. The results of the implementation of activities are divided into three main categories. First, the short-term results seen immediately after the activity are increased students' motivation and understanding of the importance of discipline. Second, the medium-term results that appear within 1-3 months are in the form of real behavioral changes, such as punctuality, neatness, and compliance with school rules. Third, long-term results that contribute to strengthening the integrity of the institution as a school with a high discipline image. Thus, this community service is expected to be able to become a model for implementing a discipline culture that is effective, sustainable, and relevant to the needs of education in Indonesia.

This study conducts a Systematic Literature Review (SLR) to explore the impact of users’ mental models on the implementation of Multi-Factor Authentication (MFA) as a strategy for mitigating password guessing risks in organizational environments. Amid the growing landscape of cyber threats, single-factor authentication has proven to be vulnerable, making MFA an essential layered security solution. However, the adoption of MFA remains slow. Existing studies indicate that expert users perceive MFA as a useful additional layer of verification, whereas non-expert users often view it as a burdensome task (a chore) and may even struggle to distinguish between different types of MFA. Dependence on mobile devices emerges as a common source of frustration for both groups. These findings emphasize that understanding users’ mental models is crucial for improving the implementation and usability of MFA. Innovations such as adaptive MFA or Single Input Multi-Factor Authentication (SIMFA) show potential as solutions to balance security requirements and user experience.

Infectious diseases remain a dynamic and evolving public health threat, requiring data-driven approaches for early detection and targeted policy planning. This study aims to model spatio-temporal trends and clustering patterns of HIV transmission in Bogor Regency during the period 2020–2023 by utilizing a combination of unsupervised and supervised machine learning techniques. The dataset was obtained from the Bogor Regency Health Office and includes annual data on the number of HIV cases across 40 sub-districts. The research methodology consists of data preprocessing stages, clustering using the K-Means algorithm, and classification using a Decision Tree model. The preprocessing steps include data integration, attribute selection, temporal aggregation, handling of missing data, and normalization using Z-score. K-Means clustering is applied to identify hidden patterns in the development of HIV cases, resulting in three distinct clusters based on multi-year trends. The resulting cluster labels are then used as target classes in the supervised classification process. The Decision Tree classification model demonstrates high accuracy in predicting cluster membership, indicating a strong relationship between the temporal patterns of HIV cases and cluster identity. The integration of clustering and classification techniques provides a robust analytical framework for understanding the dynamics of HIV transmission, while also supporting the formulation of more precise, evidence-based, and region-specific public health interventions.

Behind the success of the Free Nutritious Meal Program (MBG), there are several problems related to the health factors of the program targets, namely, there are several cases of allergies that occur in schools, inadequate understanding of allergen management owned by food processing vendors, and the high cost of laboratory tests and the process that takes a long time. So, to overcome these problems, an application is proposed that can help detect allergens in food products using data mining and machine learning approaches. SVM and AdaBoost algorithms each have advantages that can be used to help build an optimal allergen detection model. This research uses a cross-validation model validation method with a value of K = 10 to help improve the performance of the model built. In this study, from the entire fold, an average accuracy value of 98.74% was obtained. To evaluate the model built, this research has also conducted several new data inputs, and in each new data input, the accuracy value is obtained above 99%. This indicates that the model built, namely the combination of SVM and AdaBoost algorithms with the cross-validation model validation method, produces high accuracy, so this model can greatly assist the allergen detection process in food products.

Communication is a fundamental aspect of human life. However, individuals with hearing and speech impairments often face barriers in communicating with the general public. The Indonesian Sign System (SIBI) serves as a communication solution for the deaf and speech-impaired community in Indonesia, yet public understanding of SIBI remains limited. To address this issue, this study aims to develop an automatic translation model from SIBI sign language into Indonesian text by utilizing Deep Learning technology, specifically the Convolutional Neural Network (CNN) algorithm. CNN was chosen for its ability to effectively recognize visual patterns, making it suitable for processing hand gesture images in sign language. This research involved collecting and classifying a dataset of hand images based on the alphabet or words in SIBI, which were then used to train the CNN model. The designed CNN model was built to accurately classify hand signs and translate them into Indonesian text. The results of this study have the potential to serve as a supportive solution for inclusive communication between the deaf community and the wider public, and can be further developed for contextual sentence translation. Keywords: Indonesian Sign System (SIBI), CNN, Deep Learning, Automatic Translation, Inclusive Communication

Drug abuse in Indonesia is a form of social deviance influenced by psychological pressure, structural conditions, and weak social ties. This phenomenon is not only related to legal aspects but also arises as a response to stress, anxiety, and negative emotional experiences. Theories such as self-medication, escapism, Durkheim and Merton's Anomie, and Agnew's General Strain Theory suggest that drug abuse behavior can develop due to imbalanced norms, social tension, and an individual's inability to cope with life's pressures. In inmates, these factors are exacerbated by challenging social and economic experiences prior to their incarceration, increasing the risk of involvement in drug use and trafficking. This study emphasizes the need for a multidimensional approach to understanding this deviance and supporting rehabilitation and social reintegration efforts. Strengthening the roles of families, communities, and educational institutions in preventing drug abuse is crucial for providing ongoing support. A deeper understanding of the patterns of individual involvement in drug abuse is key to designing more effective prevention programs, based on psychological, social, and structural approaches to reduce the long-term impact of drug abuse on society.

This study aimed to improve the speaking skills of sixth-grade students at SDN Negeri Kelapa Dua Wetan 01 Pagi in using the Simple Past Tense pattern (was/were) through the implementation of the Role Playing method. The research was conducted in two cycles involving 32 students as the subjects. The research method used was Classroom Action Research, consisting of the stages of planning, action implementation, observation, and reflection in each cycle. Data were collected through oral pre-tests and post-tests, as well as observations of students’ learning activities during the lessons. The results showed a significant improvement in students’ speaking skills. Their average score increased from 60.3 on the pre-test to 74.1 on the post-test. The percentage of students who achieved the Minimum Mastery Criteria also rose from 31% to 75%. The Role Playing method proved effective in enhancing students’ accuracy in using was/were, improving speaking fluency, and boosting self-confidence in oral communication. In conclusion, the application of the Role Playing method had a positive and significant impact on English learning outcomes among the sixth-grade students at SDN Negeri Kelapa Dua Wetan 01 Pagi. It is recommended that teachers continue to apply this method consistently, and that schools provide additional supporting facilities to optimize the learning process. For future studies, teachers and students are encouraged to expand the variety of role-play scenarios and include a control group to obtain a deeper and more comprehensive understanding of the effectiveness of the Role Playing method.